The CHA2DS2-VASc score identifies those patients with atrial fibrillation and a CHADS2 score of 1 who are unlikely to benefit from oral anticoagulant therapy
Bibliographic record
Abstract
AIMS: The CHA(2)DS(2)-VASc score is a modification of the CHADS(2) score that aims to improve stroke risk prediction in patients with atrial fibrillation (AF) by adding three risk factors: age 65-74, female sex, and history of vascular disease. Whereas previous evaluations of the CHA(2)DS(2)-VASc score included all AF patients, the aim of this analysis was to evaluate its discriminative ability only in those patients for whom recommendations on antithrombotic treatment are uncertain (i.e. CHADS(2) score of 1). METHODS AND RESULTS: We selected all patients with a CHADS(2) score of 1 from the AVERROES and ACTIVE trials who were treated with acetylsalicylic acid with or without clopidogrel and calculated the incidences of ischaemic or unspecified stroke or systemic embolus (SSE) according to their CHA(2)DS(2)-VASc score. Of 4670 patients with a baseline CHADS(2) score of 1, 26% had a CHA(2)DS(2)-VASc score of 1 and 74% had a score of ≥ 2. After 11 414 patient-years of follow-up, the annual incidence of SSE was 0.9% (95% CI: 0.6-1.3) and 2.1% (95% CI: 1.8-2.5) for patients with a CHA(2)DS(2)-VASc score of 1 and ≥ 2, respectively. The c-statistic of the CHA(2)DS(2)-VASc score was 0.587 (95% CI: 0.550-0.624). Age 65 to <75 years was the strongest of the three new risk factors in the CHA(2)DS(2)-VASc score. CONCLUSION: The CHA(2)DS(2)-VASc score reclassifies 26% of patients with a CHADS(2) score of 1 to a low annual risk of SSE of 1%. This risk seems low enough to consider withholding anticoagulant treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".